AWSEM-Suite: a protein structure prediction server based on template-guided, coevolutionary-enhanced optimized folding landscapes

Jin, Shuang; Contessoto, Vinícius G.; Chen, Mingchen; Schafer, Nicholas P.; Lu, Wei; Chen, Xun; Bueno, Carlos; Hajitaheri, Arya; Sirovetz, Brian J.; Davtyan, Aram; Papoian, Garegin A.; Tsai, Ming-Yen; Wolynes, Peter G.

doi:10.1093/nar/gkaa356

Cited by 20 publications

(11 citation statements)

References 26 publications

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“…The AWSEM-MD simulation protocol has been used to address a variety of biological questions, such as protein structure prediction (Davtyan et al, 2012;Tsai et al, 2016b;Sirovetz et al, 2017;Chen et al, 2018a), protein binding prediction (Tsai et al, 2016b), protein aggregation (Zheng et al, 2016(Zheng et al, , 2017, as well as complex protein-DNA assemblies and remodeling (Tsai et al, 2016a(Tsai et al, , 2019Potoyan et al, 2016b;Zhang et al, 2016). Interested readers are encouraged to test the online web-server version, AWSEM-Suite for structure prediction (Jin et al, 2020). Because of openMM's extensibility in python scripting, openAWSEM benefits from such flexibility for interfacing with other post-processed analysis and visualization toolkits, such as MDTraj, pyEMMA and NGLviewer.…”

Section: Molecular Dynamics Simulation Using Openawsemmentioning

confidence: 99%

Fibril Surface-Dependent Amyloid Precursors Revealed by Coarse-Grained Molecular Dynamics Simulation

Lin

Tsai

2021

Front. Mol. Biosci.

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Amyloid peptides are known to self-assemble into larger aggregates that are linked to the pathogenesis of many neurodegenerative disorders. In contrast to primary nucleation, recent experimental and theoretical studies have shown that many toxic oligomeric species are generated through secondary processes on a pre-existing fibrillar surface. Nucleation, for example, can also occur along the surface of a pre-existing fibril—secondary nucleation—as opposed to the primary one. However, explicit pathways are still not clear. In this study, we use molecular dynamics simulation to explore the free energy landscape of a free Abeta monomer binding to an existing fibrillar surface. We specifically look into several potential Abeta structural precursors that might precede some secondary events, including elongation and secondary nucleation. We find that the overall process of surface-dependent events can be described at least by the following three stages: 1. Free diffusion 2. Downhill guiding 3. Dock and lock. And we show that the outcome of adding a new monomer onto a pre-existing fibril is pathway-dependent, which leads to different secondary processes. To understand structural details, we have identified several monomeric amyloid precursors over the fibrillar surfaces and characterize their heterogeneity using a probability contact map analysis. Using the frustration analysis (a bioinformatics tool), we show that surface heterogeneity correlates with the energy frustration of specific local residues that form binding sites on the fibrillar structure. We further investigate the helical twisting of protofilaments of different sizes and observe a length dependence on the filament twisting. This work presents a comprehensive survey over the properties of fibril growth using a combination of several openMM-based platforms, including the GPU-enabled openAWSEM package for coarse-grained modeling, MDTraj for trajectory analysis, and pyEMMA for free energy calculation. This combined approach makes long-timescale simulation for aggregation systems as well as all-in-one analysis feasible. We show that this protocol allows us to explore fibril stability, surface binding affinity/heterogeneity, as well as fibrillar twisting. All these properties are important for understanding the molecular mechanism of surface-catalyzed secondary processes of fibril growth.

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Section: Molecular Dynamics Simulation Using Openawsemmentioning

confidence: 99%

Fibril Surface-Dependent Amyloid Precursors Revealed by Coarse-Grained Molecular Dynamics Simulation

Lin

Tsai

2021

Front. Mol. Biosci.

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“…Since the currently used secondary structure prediction prescribes only three categories (helix, sheet, and coil), converting from SS3 to SS8 may help AWSEM-Suite perform better especially for the barrel-like structures and when there are helix kinks in the native structure. The AWSEM-Suite algorithm has been implemented as an online server at …”

Section: Discussionmentioning

confidence: 99%

Protein Structure Prediction in CASP13 Using AWSEM-Suite

Jin¹,

Chen²,

Chen

et al. 2020

J. Chem. Theory Comput.

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Recently several techniques have emerged that significantly enhance the quality of predictions of protein tertiary structures. In this study, we describe the performance of AWSEM-Suite, an algorithm that incorporates template-based modeling and coevolutionary restraints with a realistic coarse-grained force field, AWSEM. With its roots in neural networks, AWSEM contains both physical and bioinformatical energies that have been optimized using energy landscape theory. AWSEM-Suite participated in CASP13 as a server predictor and generated reliable predictions for most targets. AWSEM-Suite ranked eighth in both the free-modeling category and the hard-to-model category and in one case provided the best submitted prediction. Here we critically discuss the prediction performance of AWSEM-Suite using several examples from different categories in CASP13. Structure prediction tests on these selected targets, two of them being hard-to-model targets, show that AWSEM-Suite can achieve high-resolution structure prediction after incorporating both template guidances and coevolutionary restraints even when homology is weak. For targets with reliable templates (template-easy category), introducing coevolutionary restraints sometimes damages the overall quality of the predictions. Free energy profile analyses demonstrate, however, that the incorporations of both of these evolutionarily informed terms effectively increase the funneling of the landscape toward native-like structures while still allowing sufficient flexibility to correct for discrepancies between the correct target structure and the provided guidance. In contrast to other predictors that are exclusively oriented toward structure prediction, the connection of AWSEM-Suite to a statistical mechanical basis and affiliated molecular dynamics and importance sampling simulations makes it suitable for functional explorations.

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“…The AWSEM-Suite algorithm has been implemented as an online server at https://awsem.rice.edu (Jin, Contessoto et al, 2020). This server could benefit crystallographers at large, and the server documentation includes an example of how to use the server output to phase X-ray data in Phenix.…”

Section: Discussionmentioning

confidence: 99%

Molecular-replacement phasing using predicted protein structures from AWSEM-Suite

Jin

Miller

Chen

et al. 2020

IUCrJ

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The phase problem in X-ray crystallography arises from the fact that only the intensities, and not the phases, of the diffracting electromagnetic waves are measured directly. Molecular replacement can often estimate the relative phases of reflections starting with those derived from a template structure, which is usually a previously solved structure of a similar protein. The key factor in the success of molecular replacement is finding a good template structure. When no good solved template exists, predicted structures based partially on templates can sometimes be used to generate models for molecular replacement, thereby extending the lower bound of structural and sequence similarity required for successful structure determination. Here, the effectiveness is examined of structures predicted by a state-of-the-art prediction algorithm, the Associative memory, Water-mediated, Structure and Energy Model Suite (AWSEM-Suite), which has been shown to perform well in predicting protein structures in CASP13 when there is no significant sequence similarity to a solved protein or only very low sequence similarity to known templates. The performance of AWSEM-Suite structures in molecular replacement is discussed and the results show that AWSEM-Suite performs well in providing useful phase information, often performing better than I-TASSER-MR and the previous algorithm AWSEM-Template.

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AWSEM-Suite: a protein structure prediction server based on template-guided, coevolutionary-enhanced optimized folding landscapes

Cited by 20 publications

References 26 publications

Fibril Surface-Dependent Amyloid Precursors Revealed by Coarse-Grained Molecular Dynamics Simulation

Fibril Surface-Dependent Amyloid Precursors Revealed by Coarse-Grained Molecular Dynamics Simulation

Protein Structure Prediction in CASP13 Using AWSEM-Suite

Molecular-replacement phasing using predicted protein structures from AWSEM-Suite

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